自适应聚类的全耦合稀疏学习算法

在图像处理领域,基于稀疏表示理论的图像超分辨力算法、高低分辨力字典与稀疏编码之间的映射关系是其中的2个关键环节。由于丰富多样的图像类型,单一字典并不能很好地表示图像。而在稀疏编码之间的映射关系上,严格相等的约束关系也限制了图像重建的效果。针对上述两个方面,采用包容性更强的多个字典与约束条件更为宽松的全耦合稀疏关系进行图像的超分辨力重建。在图像非局部自相似性的基础上,进行多次自适应聚类;挑选出最优的聚类,通过全耦合稀疏学习的图像超分辨力算法,得到多个字典;最后,对输入的低分辨力图像进行分类重建,得到高分辨力图片。实验结果表明,在图像Leaves,Barbara,Room上,本文的聚类算法比原全耦合稀疏学习算法在峰值信噪比(PSNR)上分别提升了0.51 dB,0.21 dB,0.15 dB。     

Designing Multicolor Micropatterns of Inverse Opals with Photonic Bandgap and Surface Plasmon Resonance

Structural coloration provides unique features over chemical coloration, such as nonfading, color tunability, and high color brightness, rendering it useful in various optical applications. To develop the structural colors, two different mechanisms of coloration–photonic bandgap (PBG) and surface plasmon resonance (SPR)–have been separately utilized. In this work, a new method is suggested to create structurally colored micropatterns by regioselectively employing SPR in a single film of inverse opal with PBG. The inverse opals are prepared by thermal embedding of opal into a negative photoresist and its subsequent removal. The inverse opals have a hexagonal array of open pores on the surface which serves as a template to make SPR‐active nanostructures through a directional deposition of gold, a perforated gold film and an array of curved gold disks are formed. With a shadow mask lithographically prepared, the gold is regioselectively deposited on the surface of the inverse opal, which results in two distinct regions of gold‐free inverse opal with PBG and gold nanostructure with SPR. As PBG and SPR develop their own structural colors respectively, the resultant micropatterns exhibit pronounced dual colors. More importantly, the micropatterns show the distinguished optical response for evaporation of volatile liquids that occupy the pores.     

Physicochemical properties and oxidative stabilities of mealworm (<Emphasis Type="Italic">Tenebrio molitor</Emphasis>) oils under different roasting conditions

Physicochemical properties and oxidative stabilities of mealworm (Tenebrio molitor) oils under different roasting conditions were investigated. Oils were extracted using n-hexane from mealworms roasted at 200°C for 0, 5, 10, and 15 min and physicochemical properties and oxidative stabilities of oils were analyzed. Roasting increased the color intensity and the oleic acid and δ-tocopherol contents, but decreased linoleic acid, and α- and γ-tocopherol contents. An improvement in oxidative stability was observed in roasted mealworm oils, demonstrated by induction time and peroxide values. Mealworm oil contained abundant essential fatty acids and exhibited a superior oxidative stability.     

Carbonaceous Materials-12: a Novel Highly Sensitive Graphene Oxide-Based Carbon Electrode: Preparation,Characterization, and Heavy Metal Analysis in Food Samples

Graphene oxide (GO) was covalently attached to glassy carbon (GC) electrode (GC–O–GO) for fabricating nanosensors to determine trace Pb²⁺ and Cd²⁺ using differential pulse anodic stripping voltammetry (DPASV). Surface characterization of the nanofilm-covered electrode was performed via electrochemical cyclic voltammetry (CV), transmission electron microscopy (TEM), atomic force microscopy (AFM), and X-ray photoelectron spectroscopy (XPS) techniques. Surface pKa of the GO covalent attached GC (GC–O–GO) was calculated via CV. Under optimal conditions, a linear response was found for Pb²⁺ and Cd²⁺ in the range from 1?×?10^?8 to 1?×?10^?12 M. The limit of detections (LODs) of Pb²⁺ and Cd²⁺ were 0.25 pM and 0.28 pM, respectively. The method shows good reproducibility, and stability was successfully applied to measure Pb²⁺ and Cd²⁺ levels in rice, soya, milk, and tap water samples, with good agreement with those obtained by the standard inductively coupled plasma optical emission spectrometry (ICP-OES) method. The method was evaluated by application with the simultaneous determination of the ions in food samples (n?=?6) using the standard addition method. The recoveries of the Pb²⁺ and Cd²⁺ were up to 98 %.     

Online Blind Channel Normalization Using BPF‐Based Modulation Frequency Filtering

We propose a new bandpass filter (BPF)‐based online channel normalization method to dynamically suppress channel distortion when the speech and channel noise components are unknown. In this method, an adaptive modulation frequency filter is used to perform channel normalization, whereas conventional modulation filtering methods apply the same filter form to each utterance. In this paper, we only normalize the two mel frequency cepstral coefficients (C0 and C1) with large dynamic ranges; the computational complexity is thus decreased, and channel normalization accuracy is improved. Additionally, to update the filter weights dynamically, we normalize the learning rates using the dimensional power of each frame. Our speech recognition experiments using the proposed BPF‐based blind channel normalization method show that this approach effectively removes channel distortion and results in only a minor decline in accuracy when online channel normalization processing is used instead of batch processing.     

Structural Basis for Carbapenem-Hydrolyzing Mechanisms of Carbapenemases Conferring Antibiotic Resistance

Carbapenems (imipenem, meropenem, biapenem, ertapenem, and doripenem) are β-lactam antimicrobial agents. Because carbapenems have the broadest spectra among all β-lactams and are primarily used to treat infections by multi-resistant Gram-negative bacteria, the emergence and spread of carbapenemases became a major public health concern. Carbapenemases are the most versatile family of β-lactamases that are able to hydrolyze carbapenems and many other β-lactams. According to the dependency of divalent cations for enzyme activation, carbapenemases can be divided into metallo-carbapenemases (zinc-dependent class B) and non-metallo-carbapenemases (zinc-independent classes A, C, and D). Many studies have provided various carbapenemase structures. Here we present a comprehensive and systematic review of three-dimensional structures of carbapenemase-carbapenem complexes as well as those of carbapenemases. We update recent studies in understanding the enzymatic mechanism of each class of carbapenemase, and summarize structural insights about regions and residues that are important in acquiring the carbapenemase activity.     

Image based rainfall amount estimation for auto-wiping of vehicles

Neural Computing and Applications - With rapid development of deep learning, a lot of computer vision tasks, such as object detection and semantic segmentation, have been applied to various...     

Combined task and motion planning system for the service robot using hierarchical action decomposition

Intelligent Service Robotics - A service robot needs integration of symbolic reasoning for high-level task planning and geometric computation for low-level motion planning to provide services in an...